Stock analysis skills

SKILL效率
效率 未标注权限 许可证不明确
安装这个技能

This skill provides the methodology, analytical standards, and scoring logic for producing institutional-quality equity research reports across 10 structured modules. It is loaded automatically whenever a stock or company analysis is requested.

一句话选型结论

按资料字段整理

Stock analysis skills是效率类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类效率 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_8ef78c30/stock-analysis-skills
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

效率
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_8ef78c30仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791734580
正文体量7.4 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
整理待办与日程

把零散任务收进清单,排出优先级。

批量处理重复任务

把固定动作做成模板,重复执行。

把流程写成清单

把口头流程整理成可复用的步骤。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在效率场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
Stock analysis skills当前 未标注权限 未标注 未标注 未标注 有
Nano PDF 文档 联网访问 ClawHub 市场 424.9 万 OpenClaw 有
自动更新程序 浏览器控制 ClawHub 市场 296.4 万 OpenClaw 有
Gemini 助手 联网访问 ClawHub 市场 254.7 万 OpenClaw 有
word DOCX 文档 联网访问 ClawHub 市场 239.6 万 OpenClaw 有
Excel XLSX 前端 联网访问 ClawHub 市场 227.0 万 OpenClaw 有

SKILL.md 全文

7.4 KB
模型实际读到的说明书原文,来自技能仓库

Stock Analysis Pro — Analytical Framework

This skill provides the methodology, analytical standards, and scoring logic for producing institutional-quality equity research reports across 10 structured modules. It is loaded automatically whenever a stock or company analysis is requested.


Core Analytical Principles

Apply these principles across every module of every report:

  • Data-first: Ground every assertion in current financial data, market data, or explicitly sourced intelligence. Do not make claims without evidence.
  • Multi-dimensional: No single factor determines an investment case. Integrate macro, technical, fundamental, valuation, and sentiment signals before forming a view.
  • Balanced: Present both bull and bear cases within each module. Avoid confirmation bias — if the data contradicts the prevailing narrative, say so.
  • Transparent: Explicitly flag data gaps, estimation uncertainty, and the limits of web-sourced information. Use ⚠️ where data is unavailable or estimated.
  • Actionable: Every module ends with a Key Takeaway. The final scorecard delivers a clear, justified investment stance — not "it depends."

The 10-Module Framework

Each module addresses a distinct analytical dimension and contributes to the overall investment verdict:

# Module Core Question
1 Macro Analysis Is the external environment a tailwind or headwind?
2 Stock Trend Analysis What is price action signaling about near-term direction?
3 Company Competency Is the business fundamentally strong with a durable moat?
4 Valuation Analysis Is the stock priced fairly relative to intrinsic value and peers?
5 Earnings & Analyst Forecast Are earnings growing and consistently beating expectations?
6 Competitor Benchmarking How does the company rank against its direct peers?
7 Risk Analysis What could go wrong and how severe are the consequences?
8 ESG & Governance Is the company sustainable and well-governed for the long run?
9 Catalyst & Event Tracker What near-term events could move the stock materially?
10 Investment Summary What is the bottom-line investment verdict with full rationale?

Scoring Logic (Module Scorecard)

Rate each module from 1 to 5 based on the analytical findings:

Score Meaning
5 Strongly positive signal — clear tailwind or outstanding quality
4 Moderately positive — good, with minor concerns
3 Neutral — mixed signals or insufficient differentiation
2 Moderately negative — notable headwinds or weaknesses
1 Strongly negative — significant concern, major red flag

Risk Profile (Module 7) is scored inversely: 5 = very low risk, 1 = very high risk.

The Overall Score is a simple average of the 9 module scores (excluding the summary module). Weighting guidance:
- For short-term theses: weight Technical Trend and Catalysts more heavily
- For long-term theses: weight Macro, Company Competency, Valuation, and ESG more heavily


Investment Stance Thresholds

Map the overall module scorecard average to a recommended analyst stance:

Overall Score Analyst Stance
4.5 – 5.0 ⭐⭐⭐⭐⭐ Strong Buy
3.5 – 4.4 ⭐⭐⭐⭐ Buy
2.5 – 3.4 ⭐⭐⭐ Hold
1.5 – 2.4 ⭐⭐ Reduce
1.0 – 1.4 ⭐ Avoid

Always articulate what would need to change for the stance to upgrade or downgrade by one level.


Data Source Hierarchy

Prioritize higher-quality sources when gathering data. Prefer recency over breadth.

  1. Company SEC filings: 10-K (annual), 10-Q (quarterly), 8-K (material events)
  2. Company investor relations pages and official earnings press releases
  3. Analyst consensus platforms: FactSet, Bloomberg, Refinitiv, LSEG (via web search)
  4. Financial data aggregators: Morningstar, Yahoo Finance, Macrotrends, Wisesheets
  5. Investment research platforms: Seeking Alpha, The Motley Fool, GuruFocus
  6. ESG rating agencies: MSCI ESG Ratings, Sustainalytics, S&P Global ESG
  7. Industry and macro data: IMF, World Bank, Federal Reserve, OECD, industry associations
  8. News and events: Reuters, Bloomberg, Financial Times, Wall Street Journal

Key Analytical Standards

Apply these standards consistently across all modules:

Financial metrics:
- Use trailing twelve months (TTM) for income statement metrics unless forward estimates are more relevant
- Compare multiples to both sector median and 3–5 year historical average for the same company
- When multiples are not meaningful (e.g., negative P/E due to losses), use EV/Sales or note the limitation
- Free cash flow yield (FCF / Market Cap) is often a more reliable signal than reported earnings multiples

Technical analysis:
- Treat indicators as confirming or diverging signals — not standalone buy/sell triggers
- RSI interpretation: >70 = overbought territory; <30 = oversold territory; divergence with price direction is more informative than absolute level alone
- MACD: focus on signal line crossovers and histogram trend (expanding vs. contracting momentum)
- Golden Cross (50-day MA crossing above 200-day MA) and Death Cross (crossing below) are significant trend signals
- Volume confirmation: price moves on high relative volume are more reliable than low-volume moves

Valuation (DCF guidance):
- Use a 2-stage or 3-stage model: near-term explicit forecast period (5 years) + terminal value
- WACC should reflect sector risk: typically 8–10% for large-cap defensive, 10–14% for growth/tech, 12–16% for speculative/small-cap
- Terminal growth rate: 2–3% for stable businesses, aligned with long-run nominal GDP growth; avoid rates above 4% without explicit justification
- Sensitivity-test the DCF on WACC ± 1% and terminal growth rate ± 0.5% to show the fair value range

Risk assessment:
- Assign risk levels (Low / Medium / High) based on both likelihood and severity of impact
- A High risk designation requires at least one of: (a) high probability of occurrence, (b) potentially company-threatening consequence, or (c) a clear near-term trigger
- ESG risk should consider both the direct financial impact of ESG failings and the reputational/regulatory overhang


Reference Files

Load these reference files for deeper methodology when needed:

  • references/macro-framework.md — Detailed macro analysis methodology: GDP, rates, inflation, regulatory landscape
  • references/technical-analysis.md — Technical indicator interpretation guide with signal tables
  • references/fundamental-framework.md — Company competency and earnings analysis methodology
  • references/valuation-framework.md — Valuation methodology including DCF construction and relative valuation
  • references/risk-esg-framework.md — Risk rating criteria and ESG/governance assessment standards

常见问题

5 问
答案由本站依据条目字段整理
Stock analysis skills怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_8ef78c30/stock-analysis-skills。安装方式为未标注。装完刷新技能列表或重开客户端。

Stock analysis skills支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

Stock analysis skills权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

Stock analysis skills收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

Stock analysis skills用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。